OBJECTIVES: To illustrate how conjoint analysis can be used to identify patient preferences for healthcare policies, and to measure preferences for healthcare reforms in Hungary. DATA SOURCE/STUDY SETTING: Data was collected via a mail-based survey and a direct survey administered in a rheumatology out-patient centre in Flór Ferenc County Hospital, Budapest, Hungary (n = 86). STUDY DESIGN: We designed and administered a conjoint analysis to the study population. Attributes and attribute levels were developed on the basis of key informant interviews and a literature review. Additional demographic, occupation and healthcare utilisation data were also collected using surveys. A mixed effects linear probability model was estimated holding respondent characteristics constant and correcting for clustering. DATA COLLECTION: Conjoint analysis questionnaires were administered by a physician to 50 consecutive rheumatology patients in a clinic and an additional 36 were mailed by post. PRINCIPAL FINDINGS: The response rate for the physician-administered survey was 98% (but 18% of these were excluded for inconsistent preferences) and 53% for the mail survey, leaving a final sample of 59. Regression results (R2 = 56.8%) indicated that patients preferred a health system that was not cost constrained (p = 0.003), was based on solidarity (p < 0.001) and where patients were empowered (p = 0.024). Further, they would choose a system with no choice of provider to avoid co-payments (p = 0.005). CONCLUSIONS: This study demonstrates that patients have clear preferences for healthcare system policy. In order to develop evidence-based healthcare policy and to empower patients in the healthcare system, methods such as conjoint analysis offer a simple yet theoretically grounded basis for policy making.
OBJECTIVES: To illustrate how conjoint analysis can be used to identify patient preferences for healthcare policies, and to measure preferences for healthcare reforms in Hungary. DATA SOURCE/STUDY SETTING: Data was collected via a mail-based survey and a direct survey administered in a rheumatology out-patient centre in Flór Ferenc County Hospital, Budapest, Hungary (n = 86). STUDY DESIGN: We designed and administered a conjoint analysis to the study population. Attributes and attribute levels were developed on the basis of key informant interviews and a literature review. Additional demographic, occupation and healthcare utilisation data were also collected using surveys. A mixed effects linear probability model was estimated holding respondent characteristics constant and correcting for clustering. DATA COLLECTION: Conjoint analysis questionnaires were administered by a physician to 50 consecutive rheumatologypatients in a clinic and an additional 36 were mailed by post. PRINCIPAL FINDINGS: The response rate for the physician-administered survey was 98% (but 18% of these were excluded for inconsistent preferences) and 53% for the mail survey, leaving a final sample of 59. Regression results (R2 = 56.8%) indicated that patients preferred a health system that was not cost constrained (p = 0.003), was based on solidarity (p < 0.001) and where patients were empowered (p = 0.024). Further, they would choose a system with no choice of provider to avoid co-payments (p = 0.005). CONCLUSIONS: This study demonstrates that patients have clear preferences for healthcare system policy. In order to develop evidence-based healthcare policy and to empower patients in the healthcare system, methods such as conjoint analysis offer a simple yet theoretically grounded basis for policy making.
Authors: John F P Bridges; Gisselle Gallego; Masatoshi Kudo; Kiwamu Okita; Kwang-Hyub Han; Sheng-Long Ye; Barri M Blauvelt Journal: BMC Health Serv Res Date: 2011-11-02 Impact factor: 2.655
Authors: Karah Y Greene; Jerome T Galea; Brandon Nguyen; Andrea N Polonijo; Karine Dubé; Jeff Taylor; Christopher Christensen; Zhiwei Zhang; Brandon Brown Journal: JMIR Res Protoc Date: 2021-11-23